In controlling customer communications in an enterprise, conventional approaches tend to make simplifying assumptions about the “preferred” channel of each customer, without paying sufficient attention to the medium and the cadence of recent communications. While rules may be triggered, it is within a limited context of customer knowledge and understanding that these are applied.
Moreover, conventional approaches are often piecemeal, with multiple silos of disparate and difficult-to-combine data about customers and interaction histories. While predictive models may be built, there is no unifying framework or sequence of actions to formulate the content, channel and timing of real-time or near-real-time customer communication. While dashboards may be present, they are typically custom-built with difficulty, without the leverage of a uniform model of historical customer interactions and outcomes.